J4 ›› 2012, Vol. 47 ›› Issue (3): 27-32.

• Articles • Previous Articles     Next Articles

Chaos particle swarm optimization based on the adaptive inertia weight

ZHOU Yan1,2, LIU Pei-yu 1,2, ZHAO Jing1,2, WANG Qian-long1,2   

  1. 1. School of Information Science and Engineering, Shandong Normal University, Jinan 250014, Shandong, China;
    2. Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology,
    Jinan 250014, Shandong, China
  • Received:2011-11-30 Online:2012-03-20 Published:2012-04-01


Aiming at the premature convergence problem which the particle swarm optimization algorithm suffers from, a chaos particle swarm optimization based on adaptive inertia weight is proposed. Firstly, chaotic sequence generated by cube map is used to initiate individual position, which strengthens the diversity of global searching. Secondly, adaptive inertia weight is adopted to improve the convergence rate. Furthermore, chaos perturbation is utilized to avoid the premature convergence. The results of the simulation experiment show that the convergence rate and the precision of the improved algorithm are obviously enhanced, and the algorithm can effectively avoid the premature convergence problem.

Key words:  particle swarm optimization; cube map; adaptive inertia weight; chaos perturbation

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